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🌳 Roadside Deforestation & Resilience: A Panarchy Framework¢

Assessing Socio-Ecological Impacts in Charghat using PRA & Geospatial PythonΒΆ

Date Location


πŸ“ OverviewΒΆ

This project investigates the severe socio-ecological crisis triggered by the widening of the Z-6006 Highway in Charghat, Rajshahi, which led to the removal of over 4,000 mature roadside trees.

Using the Panarchy Adaptive Cycle as a theoretical lens, the study integrates Participatory Rural Appraisal (PRA) with Geospatial Python (Google Earth Engine) to quantify the transition from a stable "Conservation" phase to a chaotic "Release" phase. The project assesses the cascading impactsβ€”heat stress, air pollution, and livelihood lossβ€”and co-designs a Locally Led Adaptation (LLA) framework to guide the system toward resilient "Renewal".


🎯 Objectives¢

  • Objective 1: Assess physical, socio-economic, and environmental impacts using the Panarchy Theory (Conservation $\to$ Release $\to$ Reorganization).
  • Objective 2: Validate community perceptions of heat and pollution using Remote Sensing (LST, NDVI, AOD).
  • Objective 3: Develop a community-driven Nature-Based Solutions (NBS) framework for future resilience.

πŸ› οΈ Tools & TechnologiesΒΆ

Python GEE GIS Atlas-lightgrey)


βš™οΈ MethodologyΒΆ

Step Description
1. Data Collection Primary: PRA tools (Social Mapping, FGDs, Problem Trees). Secondary: Satellite data via GEE (Sentinel-2, Landsat 8, MODIS, CHIRPS).
2. Preprocessing Used Python (geemap) to filter cloud cover, harmonize Sentinel-2 data, and compute indices (NDVI, AOD) clipped to the Charghat ROI.
3. Analysis Qualitative: Panarchy phase interpretation of community narratives. Spatial: Time-series analysis of LST (2016-2024) and Vegetation loss.
4. Visualization Created Sankey Diagrams to map causal flows of the crisis and Heatmaps to quantify stakeholder priorities.
5. Validation Triangulated PRA insights (e.g., "it feels hotter") with quantitative LST data (e.g., +5Β°C increase).

PresentationΒΆ

InΒ [10]:
 
Total Pages: 31
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πŸ“Š Results & InsightsΒΆ

  • 🌍 System Collapse: The removal of trees triggered a "Release" phase, causing a sharp decline in NDVI and a spike in Aerosol Optical Depth (AOD).
  • πŸ“ˆ Heat Island Effect: Land Surface Temperature (LST) analysis revealed that summer temperatures in 2024 reached up to 39Β°C, a significant increase from the 2016 baseline.
  • 🧭 Livelihood Shock: Code co-occurrence analysis showed that Livelihood Insecurity was the highest priority (100% intensity) for farmers and market vendors, overshadowing biodiversity concerns.

πŸ—‚οΈ Data SourcesΒΆ

Source Description Link
Sentinel-2 Vegetation Index (NDVI) 10m Copernicus
Landsat 8 Land Surface Temperature (LST) 30m USGS EarthExplorer
MODIS Terra Aerosol Optical Depth (AOD) NASA Earthdata
Primary Data FGD, KII, and Social Mapping Field Survey (Charghat, 2024)

πŸ”– TagsΒΆ

Participatory Planning Geospatial Python Panarchy Theory Google Earth Engine Climate Resilience LST Analysis Nature-Based Solutions Rajshahi